Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add JunMystery/Agent-Guidance-Python --skill accessibilitygit clone --depth 1 https://github.com/JunMystery/Agent-Guidance-PythonWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/junmystery/agent-guidance-python/accessibility)<a href="https://agentmods.dev/skills/junmystery/agent-guidance-python/accessibility"><img src="https://agentmods.dev/badge/skills/junmystery/agent-guidance-python/accessibility/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/junmystery/agent-guidance-python/accessibility"><img src="https://agentmods.dev/badge/skills/junmystery/agent-guidance-python/accessibility.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00047 | $0.01493 |
| Opus 5.5 | $0.00019 | $0.00597 |
| Sonnet 5.5 | $0.00009 | $0.00299 |
| Haiku 4.5 | $0.00005 | $0.00149 |
Grade A, and why
accessibility scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
91% identical to accessibility — 28 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Accessibility (WCAG 2.2)
This skill ensures that digital interfaces are Perceivable, Operable, Understandable, and Robust (POUR) for all users, including those using screen readers, switch controls, or keyboard navigation. It focuses on the technical implementation of WCAG 2.2 success criteria.
When to Use
- Defining UI component specifications for Web, iOS, or Android.
- Auditing existing code for accessibility barriers or compliance gaps.
- Implementing new WCAG 2.2 standards like Target Size (Minimum) and Focus Appearance.
- Mapping high-level design requirements to technical attributes (ARIA roles, traits, hints).
Core Concepts
- POUR Principles: The foundation of WCAG (Perceivable, Operable, Understandable, Robust).
- Semantic Mapping: Using native elements over generic containers to provide built-in accessibility.
- Accessibility Tree: The representation of the UI that assistive technologies actually "read."
- Focus Management: Controlling the order and visibility of the keyboard/screen reader cursor.
- Labeling & Hints: Providing context through
aria-label,accessibilityLabel, andcontentDescription.
How It Works
Step 1: Identify the Component Role
Determine the functional purpose (e.g., Is this a button, a link, or a tab?). Use the most semantic native element available before resorting to custom roles.
Step 2: Define Perceivable Attributes
- Ensure text contrast meets 4.5:1 (normal) or 3:1 (large/UI).
- Add text alternatives for non-text content (images, icons).
- Implement responsive reflow (up to 400% zoom without loss of function).
Step 3: Implement Operable Controls
- Ensure a minimum 24x24 CSS pixel target size (WCAG 2.2 SC 2.5.8).
- Verify all interactive elements are reachable via keyboard and have a visible focus indicator (SC 2.4.11).
- Provide single-pointer alternatives for dragging movements.
Step 4: Ensure Understandable Logic
- Use consistent navigation patterns.
- Provide descriptive error messages and suggestions for correction (SC 3.3.3).
- Implement "Redundant Entry" (SC 3.3.7) to prevent asking for the same data twice.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 147 lines · 47 tokens per session scan A 1e7594bd364e
accessibility is a skill published in the GitHub repository JunMystery/Agent-Guidance-Python (2 stars, last pushed 3mo ago), licensed MIT. It adds 47 tokens to every session and 1,493 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 91% identical to accessibility, differing in 28 lines, and is treated as a copy.
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